Genetic and environmental determinants of insect herbivore community structure in a Betula pendula population.

A number of recent studies have shown that intraspecific genetic variation of plants may have a profound effect on the herbivorous communities which depend on them. However less is known about the relative importance of intraspecific variation compared to other ecological factors, for example environmental variation or the effects of herbivore damage. We randomly selected 22 Betula pendula genotypes from a local population (< 0.9 ha), cloned them and planted cloned seedlings on two study sites separated at a regional scale (distance between sites about 30 km) to examine an insect community of 23-27 species on these genotypes. B. pendula genotypes did not differ in their species richness, but the total mean abundance and the structure of the insect herbivore community was significantly affected by the genotype, which could account for up to 27% of the total variation in community structure. B. pendula genotype accounted for two to four times more variation in the arthropod community structure than did environmental (block) variation on a local scale, while on a regional scale, genotypic and environmental (site) variation accounted for 4-14% of the arthropod community structure. The genetic effects were modified by environmental variation on both a local and regional scale over one study year, and locally, the largest part of the variation (38%) could be explained by the genotype × environment (block) interactions. Suppression of insect herbivores during one growing season led to changed arthropod community structure in the following growing season, but this effect was minimal and could explain only 4% of the total variation in insect community structure. Our results suggest that both genetic and environmental factors are important determinants of the community structure of herbivorous insects. Together these mechanisms appear to maintain the high diversity of insects in B. pendula forest ecosystems.

Introduction

Genetic variation within one species can affect the structure and dynamics of associated communities and entire ecosystems [1, 2]. This may be considerable, especially for keystone species, such as forest trees, which serve as food and habitat for numerous primary consumers. A vast number of studies have already shown that arthropod communities respond to genetic differences among individual plants within interspecific hybridizing complexes (e.g. Eucalyptus [3], Salix [4], Populus [5], Quercus [6]) or specific genotypes within species (e.g. Oenothera biennis [7], Eucalyptus globulus [8], Solidago altissima [9], Populus angustifolia [10]). However, it has recently been argued that the role of plant genetic variation in structuring arthropod communities has been considerably inflated due to the common methodological flaw that genotypes are collected from diverse and often distant environments, which maximizes genetic variation, whilst experiments are performed in a single common garden where environmental variation is minimized [11, 12]. Indeed, when this mismatch in scale was avoided in the experimental design, spatial processes relegated host plant genotype to a secondary role in structuring insect communities of Quercus robur L. [13]. Whether this applies to all systems is, however, not yet known.

Genes encounter a range of environments in nature and it has long been recognized that genetic determination of plant susceptibility to a herbivorous insect depends on environmental context [14]. However, most studies that have examined the role of genotype × environment interactions in the abundance and distribution of herbivorous species, have used only one or a few closely related herbivore species (e.g. [15– 18]), and much fewer studies have examined genotype × environment interactions in a community context [7, 13, 19, 20]. It is well recognized that we know too little of the relative importance of intraspecific genetic variation compared to other ecological factors that also influence multi-trophic communities and ecosystem processes [11]. Thus, the examination of genotype × environment interactions in a community context may be essential for improving our knowledge in the developing field of community genetics.

Silver birch ( Betula pendula Roth) is an ideal tree species in which to examine the mechanisms of plant-herbivore interactions and the community-level consequences of trait variation, because the species shows remarkable genetic variation in its resistance to herbivores [21– 24]. In addition, the genetic variation of secondary metabolites [26], nutrient concentrations [27], and phenological traits [28, 29] of B. pendula are known to be substantial, and all these traits are known to affect herbivores and higher trophic level interactions [2, 30, 31]. Most of the studies that have been conducted using B. pendula have used genotypes that were originally randomly selected from a local B. pendula population, i.e. from a naturally regenerated forest stand < 0.9 ha. None of these earlier studies have, however, investigated the within-population genotypic variation in B. pendula insect herbivore species richness and community composition. We cloned 22 B. pendula genotypes, planted them in two common gardens separated at a regional scale (distance between sites about 30 km), and studied the relative importance of genetic variation in community patterns, comparing both local and regional environmental variation. In addition, we examined how strongly herbivores themselves can modify arthropod communities associated with B. pendula by suppressing herbivores from half of the saplings over one growing season in one common garden and surveying their arthropod communities the following season.

Materials and methods

Plant material and study sites

The 22 different genotypes of B. pendula were cloned during spring 1998 from randomly selected B. pendula trees taken from a naturally regenerated B. pendula - B. pubescens Ehr forest in Punkaharju, southeastern Finland (61°48′ N, 29°18′ E), to study genetic variation in phenology, growth, reproduction and resistance-related traits among individual birch trees [25]. Sampling was stratified random sampling: six spots where forest lift could be transferred were first selected around the forest, and 2–5 trees within the reach of forest lift in each spot were then randomly (by throwing a coin) selected for our study purposes. B. pendula is predominantly a sexual species, but genotypes can be cloned for study purposes or for plantations using standard tissue-culture methods [32]. Cloned B. pendula saplings were planted at the growing sites (i.e. common gardens, each approximately 0.25 ha) in June 1999 to find out the degree to which the genotype and environment affect birch traits and to test how genotypes differ in their response to the environment [26]. The Kuikanniitty study site (61°47′ N, 29°21′ E) is an abandoned cultivated field and the Parikkala study site (61°36′ N, 29°36′ E) is Myrtillus type forest [33]. Soil type was defined as fine sandy till for both sites [26]. The distance between these sites was around 30 km and they were situated at approximately the same altitude (Kuikanniitty 79 m and Parikkala 93 m above sea level). Thus, the mean summer (June–August) temperatures were very similar at these sites: in 2002 mean temperatures were 17.6°C and 17.9°C and in 2003 they were 15.9°C and 15.6°C in Kuikanniitty and Parikkala, respectively. Both study sites were divided into six blocks, each of which included four saplings from each genotype. To prevent edge effects, the experimental saplings were surrounded by one row of extra saplings. From each block, one of the four saplings of a total of 22 genotypes was randomly selected for the present study in order to have six replicates per genotype.

In addition, we collected additional data from Kuikanniitty in 2003 to investigate the effect of previous insect herbivory on insect community structure and abundance, and surveyed one extra sapling from each block and genotype. These extra saplings were protected from insect herbivory in the previous growing season by regular sprayings with synthetic pyrethrin [23], which has no direct or side effects on the growth or chemistry of birch seedlings [34].

Measuring insect abundance and species richness

The insect herbivore community of each sapling was assessed by surveying the abundance of 23 (in Parikkala 2002) or 27 (in Kuikanniitty 2002–2003, and Parikkala 2003) insect taxa from diverse orders (Lepidoptera, Hymenoptera, Coleoptera, Diptera, Hemiptera; Table 1). These taxa were generally the most abundant taxa in both sites. However, species that were rare in both sites were included in the surveys as well. Species identifications were undertaken following Saalas [35] species identification guide, using several web pages ( http://www.funet.fi/pub/sci/bio/life/insecta/index.html; http://www.leafmines.co.uk/index.htm; http://www.bladmineerders.nl/; http://www.nrm.se/) with the assistance of specialists. Euceraphis betulae eggs were counted from the side of twelve (2002) or eight (2003) topmost buds in April before budburst. However, in 2002 E. betulae eggs were counted from two saplings per genotype per block (sum of the eggs on the sides of 24 buds was used in the analysis), because regular sprayings with synthetic pyrethrin on the other sapling was started only after egg counts in both sites. Trichiosoma sp. pupae were counted in April/May when the timing of budburst of the same saplings was observed (Possen, submitted manuscript). The abundance of Eriocrania sp. was determined at the end of June, Deporaus betulae at the beginning of July and Heteropteran 1 (sap sucker) in August. Croesus septentrionalis larval colonies and the number of larvae in each colony were recorded along with Eriocrania and D. betulae measurements in both years. The abundance of all other insects were determined indirectly by counting damaged leaves at the beginning of September in both years, since the damage caused by most of the surveyed taxa remained identifiable for a long time after the initial damage.

Table 1.

Description of the 27 taxa surveyed for their abundance among 22 genotypes in Kuikanniitty and Parikkala field experiments 2002 and 2003.

		2002		2003
		Kuikanniitty	Parikkala	Kuikanniitty	Parikkala
Taxa	Identification	Total number of insects/damage counted
Lepidopteran miners/rollers
Gracillaridae 1 (miner)	Phyllonorycter cavella	282	123	53	34
Gracillaridae 2 (miner)	Phyllonorycter sp. 1	61	26	12	4
Gracillaridae 3 (miner)	Phyllonorycter sp. 2	19	7	3	3
Gracillaridae 4 (miner)	Parornix betulae	114	42	40	10
Gracillaridae 5 (miner)	Parornix sp.	30	11	20	0
Eriocranidae (miner)	Eriocrania sp.	536	2007	746	2374
Pyralidae (roller or tier)	tentatively Euzophora fuliginosella	67	77	135	142
Tortricidae (galler)	Epinotia tetraquetrana [a]	159	136	159	136
Nepticulidae (miner)	Stigmella sp. 1	40	53	7	1
Incurvanidae (miner)	Phylloporia bistrigella	125	6	30	8
Geometridae (roller or tier)	Rheumaptera hastata	11	6	4	0
Gelechiidae (roller or tier)	tentatively Teleiodes sp.	87	-	211	37
Mircolepidoptera 1 (roller or tier)		64	65	188	60
Lepidoptera 1 (roller or tier)		8	2	3	0
Lepidoptera 2 (miner)		12	-	7	3
Lepidoptera 3 (roller or tier)		0	1	13	1
Lepidoptera 4 (miner)		142	7	152	82
Coleopterans
Attelabidae (roller)	Deporaus betulae	62	14	157	133
Curculionidae (miner)	Orchestes rusci	54	127	23	12
Hymenopterans
Tenthredinidae 1 (miner)	tentatively Fenusa pumila	149	109	66	59
Tenthredinidae 2 (leaf feeder)	Hemichroa australis	167	-	52	18
Tenthredinidae 3 (leaf feeder)	Croesus septentrionalis	108	7	34	0
Cimbicidae (leaf feeder)	Trichiosoma sp.	6	2	2	0
Dipterans
Agromyzidae (miner) 1	Agromyza alnibetulae	24	11	33	6
Cecidomyiidae (miner) 1		0	0	1	19
Hemipteran
Aphidoidea (sap sucker)	Euceraphis betulae	996	2640	40	114
Heteropteran
Heteropteran 1 (sap sucker)		92	-	284	466

a E. tetraquetrana counts represent the damage during the whole lifetime of the saplings (see Materials and methods). Note also that years are not directly comparable because of the changed sampling protocol between years.

In general, the insect abundance in 2002 was determined by surveying the whole sapling. The mean height of these saplings at the end of 2002 was 253 ± 4.3 cm (mean ± SE) in Kuikanniitty and 227 ± 3.8 cm in Parikkala. Because B. pendula genotypes differ in their height and diameter growth [23] and large saplings may harbor more insects than smaller saplings, we determined the whole sapling “surface area” and used it as a covariate hereafter called “size index” in statistical analysis. Surface area was determined by photographing each sapling sideways from their southern side against a white background, converting the picture to a black and white silhouette picture in Adobe Photoshop 7.0 and determining the number of black pixels (i.e. leaf and branch area) within the picture. The number of pixels was converted to m 2 using the number of pixels of a known area as a reference. The amount of pixels significantly (p < 0.001) explained over 73% of the sapling volume [Y = (3.14 * {base diameter/2} 2 * height)/3] in both sites. The abundance of Phyllonorycter cavella, Phyllonorycter sp. 1, Parornix betulae and Parornix sp. was not examined on the whole sapling, but was determined as the damage (i.e. number of mines per each species) found within a period of 30 seconds. The period of time (30 sec) was chosen so that even the smallest saplings had leaves uncounted when the time was up.

Since the method of assessing herbivore abundance/resistance by time counts has been successfully used in the past [35, 36] we decided to use time counts to determine the abundance of almost all taxa (except E. betulae, Trichiosoma sp. and C. septentrionalis) in 2003. The same person undertook all surveys. The abundance of easily visible damage (large mines and rolls) of Eriocrania sp., D. betulae and Heteropteran 1 were determined as the number of damaged areas found within a period of 30 seconds. Epinotia tetraquetrana “knobs” in the branches of the saplings were counted within a period of 20 seconds in 2003 starting at the top of the tree. Since the “knobs” in the branches remain visible for years and we did not separate different year’s growth while surveying, the values represent the accumulation of E. tetraquetrana damage during the last few years. Therefore the same values were used in both years’ insect community analyses. The abundance of all other 20 taxa in 2003 was determined within a single time count of each sapling at the beginning of September. To examine a similar proportion of each sapling, they were divided into three size categories according to their height and number of leaves. Small saplings (average height 2.8 and 3.2 m in Parikkala and Kuikanniitty, respectively) were surveyed for 30 seconds, average sized saplings (3.5 and 3.9 m in Parikkala and Kuikanniitty, respectively) for 60 seconds and large saplings (4.5 m in Kuikanniitty, large saplings were not found in Parikkala) for 120 seconds. Surveying time was used as a covariate called size index in statistical analysis.

Data analyses

All multivariate analyses were performed with Primer 6 (Primer-E Ltd, United Kingdom). The full data matrix consists of the abundance of 23–27 (23 in Parikkala 2002) insect species in 264 saplings (22 genotypes, 6 blocks, 2 sites) that were surveyed in two consecutive years. All surveyed insect species were included in the statistical analysis when sites were tested separately, but those four species that were not surveyed in Parikkala 2002 were excluded also from Kuikanniitty 2002 data when sites were compared. Arthropod community composition data was analyzed using non-parametric multivariate analysis of variance (PERMANOVA), which is well suited to non-normal ecological data such as ours [38, 39]. Years were analyzed separately in all statistical tests, because of the changed sampling protocol between years (surveying the whole tree in 2002, using time counts in 2003). All data was fourth root transformed prior to analysis to reduce differences between common and rare species. The semimetric Bay-Curtis distance, which generally seems to provide the most meaningful measure of dissimilarity in ecological community structure [39], was used to calculate distances between each pair of observations. The resulting distance matrix was used to obtain p-values using a random subset of 4999 permutations in PERMANOVA. The permutation method was permutation of residuals under a reduced model. The statistical model was designed to test the effect of genotype, site, block (nested within site) and the interaction of genotype × site using sapling size index (sapling surface area in 2002 and surveying time in 2003, see above) as a covariate. Site was treated as a fixed factor and block and genotype as random factors in the model. In addition to these analyses, we separately tested the effect of genotype and block on insect assemblages in each site and year to calculate the proportion of variance explained by B. pendula genotype and local environment (i.e. replicated block). Additional data collected from those saplings that were protected from insect herbivory in the previous growing season in Kuikanniitty 2003, were combined with the Kuikanniitty 2003 non-treated sapling data prior to analyzing the effects of insect removal, block and genotype, and their two-way interactions with the insect assemblages with PERMANOVA. Sapling size index was used as a covariate.

To visualize the multivariate patterns among observations, non-metric multidimensional scaling (nMDS) was performed on the Bay-Curtis distances. The distance among centroids for groups of samples was determined prior to nMDS to increase clarity, e.g. when the whole data was visualized we had 88 genotype-site-year points (22 genotypes in 2 sites over 2 years) instead of 528 genotype-block-site-year points. To visualize the effect of genotype in individual site and year, we separately determined the distance among genotype centroids in each site and year and produced one nMDS plot from each of these “environments”. Additional Kuikanniitty 2003 data combined with Kuikanniitty 2003 raw data was used to visualize the effect of insect removal on insect assemblages using nMDS on the genotype centroids of those saplings that were either protected from herbivory or grown under natural herbivory.

Species richness (number of species/sapling) and total mean abundance (number of herbivores/sapling) was statistically tested by analysis of covariance using SPSS 20.0.0.1 (IBM SPSS Statistics) General Linear Models (GLM) procedure. Those four species that were not surveyed in Parikkala 2002 were excluded also from Kuikanniitty species richness and total mean abundance calculations to better enable site comparisons. Genotype and block (nested within site) were treated as random factors and site as a fixed factor in the statistical model while sapling size index was used as a covariate. Additional Kuikanniitty 2003 data combined with Kuikanniitty 2003 basic data was used to analyze the effects of insect removal, block and genotype, and their interactions with the species richness and total mean abundance. Genotype and block were treated as random factors and insect removal as a fixed factor while sapling size index was used as a covariate. Total mean abundance was log(x+1)-transformed to equalize the error variances across groups in both analyses.

Results

Study years and sites were distinctly grouped apart into two-dimensional ordination space, when the genotype centroids of different years and sites were analyzed using nMDS ( Figure 1). The MANOVA Table in turn, shows that sites had statistically significantly different insect species community composition in both years ( Table 2). Sites were also clearly different in their total mean abundance ( Table 3) and species richness (p < 0.008 for the site effect in species richness): the forest site of Parikkala had a 49–78% higher total mean abundance, but 18–25% lower species richness than the abandoned field site of Kuikanniitty in 2002–2003, respectively. These findings indicate that each year and site had significantly different herbivorous insect assemblages, thus creating different biotic environments.

Figure 1.

Non-metric MDS plot of insect assemblages of 23 species colonizing 22 B. pendula genotypes in Kuikanniitty and Parikkala 2002 and 2003.

Stress is 0.14, which indicates a good representation of the data in two-dimensional ordination plot. Each point is a centroid of six replicates. Numbers in the centre of the markers are genotype identification numbers.

Table 2.

Non-parametric MANOVA table of the effects of genotype and site on insect herbivore community structure on B. pendula saplings in 2002–2003.

Sapling size index, which is a measure of height and number of leaves (see material and methods), was used as a covariate.

	Insect herbivore community 2002				Insect herbivore community 2003
	df	SS	F	P	df	SS	F	P
Genotype	21	27700	1.26	0.04	21	33294	2.04	< 0.001
Site	1	47798	16.99	< 0.001	1	10319	7.62	< 0.001
Block (Site)	10	17826	1.70	0.002	10	18013	2.31	< 0.001
G × S	21	22242	1.01	0.466	21	22472	1.37	0.006
Size index	1	4890	4.65	< 0.001	1	8084	10.38	< 0.001
Residual	208	218510			208	162000
Total	262	344260			262	274880

Table 3.

The ANCOVA table of the effects of genotype, block and site on total mean abundance of herbivores (log[x+1] transformed) of B. pendula saplings in 2002–2003.

Sapling size index, which is a measure of height and number of leaves (see material and methods), was used as a covariate.

	Mean abundance 2002				Mean abundance 2003
	df	SS	F	p	df	SS	F	p
Genotype	21	1.10	2.82	0.011	21	0.26	1.08	0.435
Error	21	0.39			21	0.24
Site	1	1.13	14.6	0.004	1	0.59	46.7	< 0.001
Error	9.6	0.75			26.7	0.34
G × S	21	0.39	1.00	0.470	21	0.24	1.81	0.019
Error	208	3.88			208	1.30
Block (Site)	10	0.77	4.11	< 0.001	10	0.16	2.55	0.006
Error	208	3.88			208	1.30
Size index	1	0.30	16.3	< 0.001	1	0.23	36.4	< 0.001
Error	208	3.88			208	1.30

Genotypic variation and genotype × environment interactions

B. pendula genotypes were significantly different in their insect species community composition in both study years ( Table 2). In 2002, regional scale environmental (site) variation explained more of the total variation in species composition than the genotype (13.9 and 8.0%, respectively), while in 2003 the genotype explained more of the total variation than the site (12.1 and 3.8%, respectively). Significant genotype × site interaction, which explained 8.2% of the total variation, was found only in 2003. When the sites were tested separately in both years we found that the effect of genotype was significant in Kuikanniitty 2002 and both study sites in 2003 ( Table 4, Figure 2). B. pendula genotype could account for 15.8–27.0% of the total variation in community structure, while local scale environmental (block) variation explained 5.9–7.6% of the total variation in community structure ( Table 4, Figure 2).

Table 4.

Non-parametric MANOVA table of the effects of genotype and block on insect herbivore community structure on B. pendula saplings in Kuikanniitty and Parikkala 2002–2003.

Sapling size index, which is a measure of height and number of leaves (see material and methods), was used as a covariate.

	Insect herbivore community 2002				Insect herbivore community 2003
	df	SS	F	P	df	SS	F	P
Kuikanniitty
Genotype	21	33778	1.29	0.018	21	25678	1.33	0.013
Block	5	10803	1.73	0.006	5	10305	2.25	< 0.001
Size index	1	4468	3.58	0.001	1	5948	6.48	< 0.001
Residual	103	128690			103	94495
Total	130	181760			130	138930
Parikkala
Genotype	21	16771	1.08	0.297	21	29083	2.16	< 0.001
Block	5	8067	2.17	< 0.001	5	7754	2.41	< 0.001
Size index	1	1735	2.34	0.033	1	2811	4.38	0.001
Residual	104	77278			104	66834
Total	131	105910			131	107680

Figure 2.

Non-metric MDS plot of insect assemblages of 23 (Parikkala 2002) or 27 species colonizing B. pendula genotypes in a) Kuikanniitty 2002, b) Parikkala 2002, c) Kuikanniitty 2003 and d) Parikkala 2003. Each point is a centroid of six replicates. Numbers in the centre of the markers are genotype identification numbers. White circles denote genotypes in Kuikanniitty, black circles denote genotypes in Parikkala. Stress values >0.2 indicate that this data may be better visualized with more dimensions (stress for three-dimensional solutions varied between 0.14 to 0.16).

B. pendula genotypes also significantly differed in their total mean abundance of herbivores (mean number of herbivores/sapling): the total mean abundance of the most susceptible genotype was 5.4- and 3.2-fold compared to the total mean abundance of the most resistant genotype in Kuikanniitty and Parikkala 2002, respectively ( Table 3, Figure 3). In 2003, only the genotype × site interaction was statistically significant, which indicates that the genotype effect strongly depended on the study site. Indeed, when we tested the study sites separately, genotype effect was significant only in Parikkala (ANCOVA: Parikkala F 21,104=2.29, p=0.003; Kuikanniitty F 21,103=1.48, p=0.103). The species richness (number of insect species/sapling) was not significantly affected by the B. pendula genotype or genotype × site interactions in either year (p>0.134).

Figure 3.

Mean abundance of insect herbivores (±SE) among B. pendula genotypes in Kuikanniitty and Parikkala study sites in 2002–2003.

White bars: Kuikanniitty, black bars: Parikkala.

Local scale genotype × environment interaction (i.e. the interaction of genotype × replicated block) was studied in Kuikanniitty 2003. Insect species community composition was significantly affected by both genotype and genotype × block interaction ( Table 5). Genotype variation explained 10.6% and genotype × block variation 38.0% of the total variation in insect community composition, indicating that genotype effect is also strongly affected by local scale environmental variation. Total mean abundance or species richness was not affected by genotype or genotype × block interaction (p>0.097).

Table 5.

Non-parametric MANOVA table of the effects of genotype, block and previous year insect removal on insect herbivore community structure among B. pendula saplings in Kuikanniitty 2003.

Sapling size index, which is a measure of height and number of leaves (see material and methods), was used as a covariate.

	df	SS	F	P
Genotype	21	30358	1.39	0.004
Insect removal	1	12525	7.11	< 0.001
Block	5	10930	2.13	< 0.001
G × IR	21	15557	0.90	0.743
G × B	104	109030	1.27	0.002
IR × B	5	6031	1.46	0.069
Size index	1	2078	2.52	0.023
Residual	103	84964
Total	261	286640

Effects of the previous year’s herbivory on insect communities

Previous year herbivory changed the insect community composition of B. pendula saplings ( Table 5). The genotype centroids of those saplings that were either subjected to natural herbivory or protected from it were located on the opposite sides of the two-dimensional nMDS ordination plot, although overlapping is evident ( Figure 4). Previous year herbivory did, however, explain only 4.4% of the total variation in insect community composition. Total mean abundance was affected by the previous year’s herbivory as well, but species richness was not (ANCOVA: effects of insect removal on total mean abundance F 1,5.28=34.6, p=0.002 and species richness p>0.829).

Figure 4.

Non-metric MDS plots of insect assemblages of 27 species colonizing 22 B. pendula genotypes that were either subjected to natural herbivory or protected from herbivory in the previous growing season in Kuikanniitty 2003.

Each point is a centroid of six replicates. Numbers in the centre of the markers are genotype identification numbers.

Correlations between species

The associations between insect species across genotypes in different sites and years seemed to be based on random associations, since we found only one correlation that was significant after sequential Bonferroni correction [40]. An unidentified gallery mine (Lepidoptera 4) and E. fuliginosella were correlated across genotypes in Kuikanniitty 2002 (Pearson’s correlation; in 2002, r = 0.88, n = 22, p < 0.0001; in 2003, r = 0.545, n = 22, p = 0.009), but not in Parikkala (p>0.199).

Community structure of insect herbivores on different genotypes of silver birch (Betula pendula)

2002_Data: Abundances of 23 individual insect species on 22 birch genotypes planted in 6 blocks in both Kuikanniitty and Parikkala study sites in 2002. Data also contain the columns for species richness and total mean abundance. Those four species that were not surveyed in Parikkala 2002 were excluded from Kuikanniitty species richness and total mean abundance calculations to better enable site comparisons. Columns containing species counts are named as in Table 1 in the associated article. Site: 1=Kuikanniitty, 2=Parikkala

2003_Data: Abundances of 27 individual insect species on 22 birch genotypes planted in 6 blocks in both Kuikanniitty and Parikkala study sites in 2003. Data also contain the columns for species richness and total mean abundance. Columns containing species counts are named as in Table 1 in the associated article. Site: 1=Kuikanniitty, 2=Parikkala.

2003_Additional_KuikanniittyData: Abundances of 27 individual insect species on 22 birch genotypes planted in 6 blocks in Kuikanniitty. Each block has two saplings from each genotype: one that was sprayed with pyrethrin in 2002 and one non-sprayed control. Data also contain the columns for species richness and total mean abundance. Columns containing species counts are named as in Table 1 in the associated article. Insecticide: 0=control, i.e. natural herbivory, 1=herbivores removed by pyrethrin sprayings in 2002. Site: 1=Kuikanniitty.

Click here for additional data file.

Discussion

Our results provide evidence that genetic variation within a natural B. pendula population can modify the structure of the arthropod community even though all genotypes supported similar insect species richness. Genetic variation in phenotypic plasticity, however, seemed to be the major factor affecting the abundance and structure of the insect herbivores associated with this tree species, because genotype effect was often dependent on the environmental variation at both regional ( Table 2 and Table 3) and local scales ( Table 5). Those B. pendula genotypes that were used in our study should give unbiased estimates of the true variance that is present in B. pendula populations, since we chose them randomly from one naturally regenerated population stand (< 0.9 ha) in eastern Finland, where this Eurasian deciduous tree species is particularly abundant [42]. By contrast, we might have exaggerated the role of regional environmental variation and genotype × environment (site) interactions by planting our genotypes on two rather different areas (open forest and abandoned field, areas that are typically rapidly colonized by B. pendula) at a much larger scale (70,000 ha). Therefore, it is not surprising that the importance of the genetic variation in structuring insect herbivore communities of B. pendula decreased from 15.8–27.0% (of variation explained) to 8.0–12.1% with increasing spatial scale in our study. Other studies have also found that while the effect of a genotype can be clear on local scales (within common gardens), it may be partially swamped by environmental variation on larger scales [7, 43].

It has been argued that, because host plant genotypes have often been collected from large geographic areas and studied within the confines of a single common garden, the role of the host plant genotype in arthropod community patterns has been largely overestimated [12]. Indeed, Tack et al. [13] showed that spatial processes dominated genetic effects when genotypes of Q. robur were collected at the same local (500 ha) or regional (1 million ha) scale as that where experiments were conducted, and thus, in real landscapes, spatial impacts might relegate host plant genotype to a minor role. Our results, however, suggest otherwise, because genotype explained about three times more of the total variation in insect herbivore community structure than local environment (block) in both sites ( Table 4), and the scale of our common garden(s) was approximately the same as the scale of that where genotypes were collected (< 0.9 ha). In addition, on a regional scale, genetic and environmental effects explained similar proportions of the total variation in arthropod community structure ( Table 2), even though we might have inflated the role of the environment in our study. This discrepancy in our results might perhaps be attributed to the difference in the distribution of these wind-pollinated tree species: the populations of Q. robur are strongly fragmented and grow at the northern margin of the species’ European distribution in southern Finland (where Tack et al. [13] conducted their experiments), while B. pendula has a wider and more continuous distribution over the whole of Finland, apart from Lapland. Q. robur populations exhibit higher geographic differentiation estimates, F st 0.032 for B. pendula and 0.066 for Q. robur [44, 45], which means that the gene flow among B. pendula populations is two times higher than among Q. robur populations, and thus local B. pendula populations might express a larger amount of genetic variation than populations of Q. robur.

We found that insect herbivore communities can be affected by both local and regional genotype × environment interactions, at least in some years. But why do B. pendula genotypes support different insect communities in different environments? It is possible that resistance traits of the genotypes are changed due to differences in abiotic environment and insect communities respond to these changes. This is supported by the fact that earlier studies have found regional genotype × environment interactions in the secondary metabolites of the same study saplings [26]. Yet, we do not know whether genotype × environment interactions in B. pendula resistance traits exist at a local scale and recent studies suggest that secondary metabolites are not the most important anti-herbivore defence of plants [31]. On the other hand, spatial processes might affect local insect communities and create genotype × environment interactions. For example, in our experiment where genotypes of each block are arranged randomly, the effects of a particular genotype could be partially masked by the effects of their conspecifics in some blocks if nearby genotypes are very dissimilar, i.e. there is associational resistance (see a review by Agrawal et al. [46]) at the level of a genotype. Both of these processes may be affecting different insect species differently. We found only one species pair that was correlated across genotypes in one of our study sites, which, together with earlier findings [47, 48], indicates that generalized defenses against multiple insect species are not likely in B. pendula (see Leimu and Koricheva [49]). Additionally, it may also be that local insect communities differ in their response regardless of spatial processes and without any change in the traits of B. pendula.

The size of B. pendula trees is positively associated with their fitness, i.e. seed production [29]. It has been shown that herbivores can reduce the growth of B. pendula by up to 46% (Mikola et al. unpublished results, see also Prittinen et al. [22], Silfver et al. [23]) and increase seedling mortality considerably [50]. Thus, by imposing selection in various genetically variable resistance traits of B. pendula [25, 26, 51], herbivores may have high potential to drive the community evolution in B. pendula. Indeed, we found that only one season of protection from herbivory changed arthropod community variables (mean abundance and community composition) in five-year old field-grown B. pendula saplings. Total mean abundance, for example, was lower in saplings that were protected from herbivory in the previous growing season, which indicates that they may have had more resources to defend themselves against insects when herbivores were present again. Yet, the magnitude of these effects was smaller than the effects of local environmental (block) variation, and could explain only about 4% of the total variation in arthropod community structure. It is important to note, however, that in nature B. pendula seedlings typically establish in open patches, where high numbers of individuals compete heavily before self-thinning eliminates some of the seedlings. Surviving for these first years and consequently reaching maturity is crucial for an individual’s fitness in this long-lived tree species. Earlier studies that have used open-pollinated progeny of the same genotypes, have shown that in such dense stands, even moderate levels of insect herbivory can change the genetic structure of B. pendula populations in the first year of establishment [52]. This is reminiscent of recent studies, which have demonstrated that natural selection can favour different genotypes in the absence of herbivores rather than in their presence, and different genotypes in response to different herbivore species within only few generations of annual or biannual plants [53, 54] (see also Hare [55]).

To conclude, we have shown that the structure of insect herbivore communities can be significantly affected by intraspecific genetic variation when there is no mismatch in scale. However, genetic effects were modified by environmental variation on both a local and regional scale in one study year. Furthermore, insect herbivore damage in one growing season changed the community patterns of the following season, yet those effects were minimal compared to genetic and environmental factors. Our results suggest that both genetic and environmental factors are important determinants of the community structure of herbivorous insects. Together these mechanisms appear to maintain the high diversity of insects in B. pendula forest ecosystems.

Data availability

figshare: Community structure of insect herbivores on different genotypes of silver birch ( Betula pendula), http://dx.doi.org/10.6084/m9.figshare.915332 [56]

This is an interesting study on the role of tree genotypes on herbivorous insect attack of willow trees, Betula pendula, using a common garden approach in Finland. Twenty-two trees were randomly selected and cloned, although no details are given as to how the trees were cloned. Each tree is considered to be a different genotype. Six blocks with 4 saplings of each genotype were used from which one sapling was randomly selected to give 6 replicates per genotype for the study of insect attack. Insect sampling was done largely based on the damage done over the summer. I am surprised that it is possible to distinguish insects based on their damage as I would have guessed that the damage from leaf miners would have been similar, and damage from sucking insects difficult to find at all. I have the following questions and comments:

What is meant by structure of the insect community? This term is used in the abstract and throughout the paper but it is not defined.

The term local environmental variation is mentioned, and it would be clearer if this was referred to as variation among blocks.

Insects were removed from some saplings but details are lacking on how this was done, how frequently it was done, and how effective it was.

“Additional Kuikanniitty 2003 data combined with Kuikanniitty 2003 raw data was used” I don’t understand what this means.

How would these results be interpreted by one who wanted to select for herbivore resistance among tree genotypes? Is the amount and consistency of the among genotype resistance sufficient to evolve over time?

How are the results influenced by variation in insect abundance from year to year?

I have read this submission. I believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

In this study, the authors selected and cloned 22 silver birch genotypes and planted them at two common garden sites to examine the effects of both genetic and environmental factors on the community structure of insect herbivores. By selecting genotypes from a spatially limited area (< 9 ha), and by performing the experiments at two spatially separated common garden sites, the authors were able to examine more precisely the main and interacting effects of genetic and environmental variation on the herbivore community. The authors also excluded herbivores on half of the host trees at each common garden site through application of an insecticide, which allowed them to examine the effect on the herbivore community in the following year.

One limitation of the study is the use of only two common garden sites, which does limit the broader implications of the study. However, despite these limitations, the data still provide sound preliminary information on the importance of both genetic and environmental variation on the structure of the herbivore community.

Although I understand and appreciate the challenges of documenting the herbivore community and the labor involved to do so, more comments are needed to address the lack of a more temporally robust sampling regime. Some species were sampled at a specific time given their respective seasonality, but most were sampled at the end of the growing season in the fall. In doing so, I suspect that authors would have missed spring and summer feeders, such as the winter moth for example, whose damage could have been difficult to ascertain and differentiate from other herbivores when herbivore damage was examined in the fall. This is not a fatal flaw, especially since the authors incorporated herbivore exclusions, which presumably would have also excluded spring and summer feeding herbivores. However, since one goal of the study was to examine the role of the herbivore community in affecting the community in the following year, it would be helpful to discuss the potential limitations of the fall sampling regime in documenting insects that feed earlier, and how the herbivore exclusion component was also (presumably) a mechanism to deal with sampling limitations. On a related note, it wasn't clear to me if potential temporal autocorrelation in the numbers and diversity of the herbivore community from one year to the next was appropriately addressed in the analysis; if so, I would suggest adding a statement in the materials and methods how this was addressed or if not, why it did not need to be addressed.

Overall, this was a nicely designed experiment, the manuscript was very well written, and the data were well presented. This study adds to our knowledge of the role of genetic and environmental variation on the structure of the herbivore community on silver birch, and sets the stage for a number of interesting follow-up questions.

I have read this submission. I believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.